A drug delivery system typically consists of a drug delivery unit and a drug dose controller. In this context, the drug delivery unit refers to a mechanical arrangement that delivers drugs to a patient. It may be, for example, a manually or actuator operated syringe, a volume controlled infusion pump, or an evaporator with an anesthesia gas circuit in an anesthesia machine. A drug dose controller in turn refers to a set-up, which may be based on an automated program, an algorithm, or on a decision-making or support tool, which adjusts the dose to a desired level for the patient.
In target controlled infusion (TCI) the operator sets a target concentration of the drug for the patient and an automated controller drives the concentration to the target level by optimally adjusting the infusion rate of a pump. In drug effect monitoring or estimation, a set-up comprising a sensor, a monitor, and a display measures and estimates the effect of a drug in the patient and informs the user about the effect. At present, such estimation or monitoring units are not generally available.
In anesthesia, during which drugs affecting the central nervous system, typically hypnotics and analgesics, are administered, direct measures of drug effects do not exist. However, estimators of the drug effects can be found from physiological or neuro-physiological parameters, which are indirectly indicative of the drug effects in brains. For instance, today the level of consciousness can be reliably estimated based on the EEG measured from the patient. In connection with intra-venous (IV) anesthesia it has also been suggested that the drug concentration in the patient may be estimated by pharmacokinetic (PK) modeling of the drug concentrations in body, from which the effect in brains is predicted using a pharmocodynamic (PD) model. The PK/PD models, which predict drug effects in brains, use certain patient stimulations, such as laryngoscopy, to induce patient responses, and relate the probability of the response to the effect site or plasma drug concentration. The PK/PD model is thus based on the probability of patient response to certain stimulation or certain clinically relevant event, such as loss of consciousness (LOC), in a large patient population.
In operating theatres, a typical drug delivery system is an anesthesia machine or workstation, in which inhaled anesthetic agents are administered using an agent evaporator, i.e. a delivery unit, which is controlled either electronically by a control unit or manually based on measured end-tidal anesthetic agent concentrations and on the concept of Minimum Alveolar Concentration (MAC). The MAC, which is similar to the stimulus-response PK/PD approach, is a statistical measure for the anesthetic agent end tidal concentration at which 50 percent of all patients loose movement response to surgical incision. In present-day intra-venous anesthesia blood plasma or effect site concentrations cannot be continuously measured, which leaves the PK/PD models and clinical observations as the only tools for estimating the drug effects.
Basically, two different control methods are used for the administration of drugs. In an open loop system an anesthesiologist or a physician makes a decision to maintain or change drug concentration based on patient responses, i.e. based on clinically relevant visible effects and a direct or indirect monitoring of vital signs, in particular heart rate and blood pressure. Clinical decisions are often based on certain clinical rules, for instance triggered by a change of blood pressure to a 10 percent higher level than the patient baseline values, or the said decisions are assisted by an automated support system based on similar rules. In a closed loop system, the drug delivery units are automated units, in which a computer program acting as a dose controller controls the drug administration based on measured values of a control variable and the desired set point of the said variable.
In anesthesia and in intensive care units, the drugs delivered by the drug delivery units are typically analgesics, which induce pain relief or antinociception in the patient, hypnotics, which control the depth of sleep or hypnosis, and relaxants, which paralyze the patient. The assessment and control of the level of hypnosis, antinociception, and muscle relaxation constitutes the foundation of modern anesthesia. All typical drugs in anesthesia could be controlled either in an open loop or in a closed loop manner, though commercially validated and approved decision support tools or automated closed loop systems do not exist at present.
There are many basic difficulties in designing a well-performing closed loop system. First, a suitable control variable, which could reliably measure the clinical end effect in the patient, may not be available. Second, due to the complexity of the human body, there is usually not a good single-valued relationship between the pharmaceutical effect site drug concentration and the desired clinical effect. Third, because of the human variability, the pharmaceutical effect site concentration cannot be reliably estimated by the current rather inaccurate general-purpose pharmacokinetic models. Fourth, the design of an accurate, reliable and easy-to-use controller or actuator for the drug delivery is difficult. Fifth, an automated computer program has many interrelated device and patient parameters, which should be known in order to achieve a timely and quantitatively precise delivery of right drugs at right instants and in right doses for each patient.
The design of a fully or partially automated drug delivery system for controlling the muscle relaxation in a patient is, perhaps, the easiest one to achieve. Muscle relaxation is usually achieved by neuromuscular blocking agents (NMBA), which block the neuronal impulse traffic at the muscle-nerve junctions. A complete neuromuscular block paralyzes the patient and thus allows surgery on immobilized body parts.
The level of the neuromuscular block may be measured by monitoring neuromuscular transmission (NMT). This may be done by electrically stimulating a motor nerve, usually the Ulnar nerve of the forearm, and measuring or observing a movement response of the patient hand. Various stimulation modes are available, including a train-of-four (TOF) stimulation in which the fading of the response is measured using four consecutive electric stimuli on the motor nerve. TOF and other neuromuscular blockade estimates are relatively good control parameters for the automated NMBA delivery, as they measure the drug effect (transmission of the neuronal signal to the muscle) in the patient rather directly. The set point of the control parameter value is usually based on a population mean data. NMT may presently be measured continuously in modern anesthesia monitors, such as the Datex-Ohmeda S/5 Anesthesia Monitor. With continuous and reliable NMT measurement a good closed loop control system is thus in principle possible. The neuromuscular blockade may also be measured by using a hand-held stimulator and observing the movement response of the stimulated body part. These devices are suitable for open loop control only.
Hypnosis is an artificially induced altered state of consciousness, which resembles sleep. In anesthesia, the level of hypnosis is controlled by induction of sedative drugs or anesthetic agents. Hypnosis always refers to the suppression or alteration of the (cortical) brain functions. The depth of hypnosis can be clinically tested by non-noxious stimulation of the patient, such as loud speak or light squeeze, shake or touch, and by observing the patient responses, such as eye opening, communication ability, etc. Hypnotic drugs, however, always increase the overall inhibitory neuronal functions, as they usually affect the GABA (gamma-aminobutyric acid) system in the brains. Therefore, the hypnotics suppress both the cortical and subcortical activities in the brains. As a consequence, also the autonomic and reflex functions in the brains are altered and suppressed. This mechanism may be one reason explaining the interaction and the resulting large synergic effect between opioids and hypnotics.
The depth of hypnosis is not directly measurable. Therefore, drug delivery systems have to derive the level of hypnosis from a surrogate signal or from indirectly measured parameters. The most common and popular surrogate signal for this purpose is the EEG (electroencephalogram), from which several parameters, such as the spectral edge frequency (SEF), may be determined. The basic reason for the insufficiency of a single parameter is the variety of drugs and the complexity of the drug effects on the EEG signal in human brains. However, during the past few years, some commercial validated devices for measuring the level of consciousness and/or awareness in clinical set-up during anesthesia or sedation have become available. Two of these devices, which are based on a processed EEG signal but which examine the signal as a whole with its multiple features, have been introduced by Aspect Medical (Bispectral Index) and by Datex-Ohmeda (Entropy Index). Furthermore, a device, an auditory evoked EEG response monitoring device (AAI™) using an active EEG response measurement has been introduced by Danmeter. At present, the situation with the assessment of the level of hypnosis is considered satisfactory, though not fully resolved for such demanding applications as those related to the automated drug delivery. As mentioned above, the hypnotic and analgetic drugs interact and have synergic effects, which call for a multi-parameter input-output drug delivery control. The control of the adequacy of anesthesia is a real challenge, since optimal patient care during surgery or intensive care requires simultaneous adjustment of hypnosis and analgesia.
The assessment and control of the level of analgesia during anesthesia is the least understood component needed for automated drug delivery. Today, no such automated systems exist or no control attempts have been made. Nociception from a damaged tissue site is transmitted to the Central Nervous System (CNS) via several different ascending pathways causing responses that may be cortical pain responses or subcortical stress responses. The stress responses to noxious stimuli may be moderated by the suppression of the pain signal pathways by opioids at the subcortical level, often in the region of the brainstem and spinal cord. In this context, antinociception refers to the blocking or suppression of nociception in the pain pathways at the subcortical level. Both cortical (pain and hypnosis) and subcortical (antinociception) mechanisms play a substantial role in pain management in modern surgical anesthesia and intensive care.
At present, the level of nociception or antinociception or the overall surgical stress cannot be measured. Observations of the blood pressure and heart rate in the patient correlate somewhat with the level of analgesia during anesthesia, but still no objective measures of analgesia exist. The drug delivery control systems used in anesthesia therefore usually ignore the analgesic component and focus on the control of the depth of hypnosis with heuristic administration of analgesic drugs through boluses or infusion.
The need for reliably monitoring of the adequacy of anesthesia and delivering the right drugs in right doses at right instants of time in order to control and balance the anesthesia is based on the quality of patient care and on economy related aspects. Balanced anesthesia reduces surgical stress and there is firm evidence that adequate analgesia decreases postoperative morbidity. Awareness during surgery with insufficient analgesia may lead to a post-traumatic stress disorder. From economical point of view, too deep an anesthesia may cause increased perioperative costs through many side-effects and extra use of drugs and time mainly in the post-operative care. Too deep a sedation may also cause complications and prolong the usage time of expensive facilities, such as the intensive care theater.
U.S. Pat. No. 6,801,803 discloses a method and device for ascertaining the cerebral state of a patient. In this disclosure, a measure derived from EMG signal data enhances and confirms the determination of the hypnotic state made using EEG signal data. As the EMG data may be computed more frequently than the EEG data, this renders ascertaining changes in the hypnotic state of the patient more rapid. State entropy (SE), which is calculated in the low frequency band up to 32 Hz, is dominated by the cortical EEG activity, while response entropy (RE), which also includes the high frequencies up to 47 Hz, represents both the cortical and muscle activity. The difference RE-SE is, therefore, a measure of the (f)EMG power, which will increase at nociception and which, therefore, may be a good measure of the suppression of the pain pathways. However, the above-mentioned dependency on the medication of the patient may render the method unusable in certain situations. As the (facial) electromyography signal is affected by neuro-muscular blocking agents (NMBAs), which suppress signaling at the nerve-muscle junctions, the EMG component of the measurement may vanish and render the method unusable, if the medication of the patient includes neuro-muscular blocking agents. Furthermore, the difference RE-SE is not specific to the suppression of the pain pathways but also reflects the overall motoric activity following any arousals—that is emotional or normal sensory evoked arousals, too. For instance, when the patient is awake and not perceiving any pain or discomfort, the RE-SE difference is typically about 8 to 10 percent. At deep hypnosis it is obvious that only painful stimuli can cause RE to differ from SE, but it is difficult to tell at which level the transition to the only-nociception induced varying difference in the deep anesthesia takes place. Furthermore, the RE-SE difference often behaves in an on-off manner without dynamic grading in between the on and off states. Therefore, the said difference suits better for event counter type applications, whereas it is less usable as a control variable for drug delivery.
U.S. Pat. No. 6,631,291 discloses a drug administration method and apparatus, in which the determination of the hypnotic level is based on a measure of the complexity of EEG signal data measured from a patient. The said measure, such as Spectral State Entropy (SE), is then used as the control variable for the delivery of a hypnotic drug. The said patent also suggests that in conjunction with the complexity of the EEG signal a measure of the electromyographic (EMG) activity of the patient may be used to improve the response time of the determination of the level of hypnosis and to speed up the control of the drug. However, U.S. Pat. No. 6,631,291 does not suggest the administration of an analgesic drug, which may have a considerable synergic effect on the level of hypnosis in the patient and, more importantly, might be the drug which, instead of a hypnotic drug, may lead to a better and balanced anesthesia in the patient. The adequacy of anesthesia in the central nervous system of a patient is thus a two-dimensional state, which should be controlled both by hypnotic and analgesic drugs in order to achieve an optimum balance for different patients, all reacting individually to these drugs.
U.S. Pat. Nos. 4,828,551 and 5,957,885 describe patient controlled analgesia (PCA) units, by which analgesic drugs are administered to the patient. The patient him- or herself controls the units to his or her optimum analgesics delivery. Therefore, the patient operating the device must be conscious to perceive and experience the pain from the tissue damage, and to relieve the pain by pressing a button or other type of delivery control actuator to release a bolus of the drug.
The prior art technology thus aim to describe the adequacy of anesthesia using a unidimensional concept for the anesthesia. Prior art solutions do not account for separate hypnotic and analgesic components, which are orthogonal, i.e. as much independent of each other as possible, and specific to the hypnotic and analgesic medications given during anesthesia. Thus the prior art methods cannot not answer the question, whether one should add or reduce the analgesics or hypnotics in order to restore a balanced anesthesia. Nowadays, personalized anesthesia requires that the anesthesiologist knows not only which drug but also how much and when to administer the drug, and that the corresponding control variables, which measure the effect of the drug choices on patient state, are available to support or directly control the drug administration.
The present invention seeks to alleviate or eliminate the above drawbacks and to bring about a novel mechanism for monitoring, evaluating and controlling anesthesia with balanced delivery of hypnotics, analgesics, and muscle relaxants.